"BXC (Bendix Carstensen)" <[EMAIL PROTECTED]> writes: > > It's important to remember that lnL is defined only up to an additive > > constant. For example a Poisson model has lnL contributions -mu + > > y*log(mu) + constant, and the constant is arbitrary. The > > differencing > > in the deviance calculation eliminates it. What constant would you > > like to use?? > > > > I have always been und the impression that the constant chosen by glm is > that which makes the deviance of the saturated model 0, the saturated > model being the one with one parameter per observation in the dataset.
As David pointed out, the deviance of a saturated model is zero by definition. However, there's nothing arbitrary about the constant in a likelihood either since it is supposed to be a density if seen as a function of y (well, if you *really* want to quibble, it's a density with respect to an arbitrary measure, so you could get an arbitrary constant in if you insist, I suppose). The point is that the constant is *uniformative* since it depends on y only, not mu, and hence that people tend to throw some bits of the likelihood away, and not always the same bits. -- O__ ---- Peter Dalgaard Blegdamsvej 3 c/ /'_ --- Dept. of Biostatistics 2200 Cph. N (*) \(*) -- University of Copenhagen Denmark Ph: (+45) 35327918 ~~~~~~~~~~ - ([EMAIL PROTECTED]) FAX: (+45) 35327907 ______________________________________________ [EMAIL PROTECTED] mailing list https://www.stat.math.ethz.ch/mailman/listinfo/r-help PLEASE do read the posting guide! http://www.R-project.org/posting-guide.html
